Remote sensing estimation of the concentration and sources of coloured dissolved organic matter based on MODIS: A case study of Erhai lake

Abstract. Given the importance of dissolved organic matter (DOM) in the carbon cycling of aquatic ecosystems, information on its seasonal variability is crucial. In this study we assess the use of optical absorption indices available in the literature based on in situ data to both characterize the seasonal variability of DOM in a highly complex environment and for application in large-scale studies using remote sensing data. The study area comprises four lakes located in the Mamirauá Sustainable Development Reserve (MSDR). Samples for the determination of colored dissolved organic matter (CDOM) and measurements of remote sensing reflectance (Rrs) were acquired in situ. The Rrs was used to simulate the response of the visible bands of the Sentinel-2 MultiSpectral Instrument (MSI), which was used in the proposed models. Differences between lakes were tested using the CDOM indices. The results highlight the role of the flood pulse in the DOM dynamics at the floodplain lakes. The validation results show that the use of the absorption coefficient of CDOM (aCDOM) as a proxy of the spectral slope between 275 and 295 nm (S275–295) during rising water is worthwhile, demonstrating its potential application to Sentinel-2 MSI imagery data for studying DOM dynamics on the large scale.

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Use of absorption optical indices to assess seasonal variability of dissolved organic matter in amazon floodplain lakes

10.5194/bg-2019-324 ◽

2019 ◽

Author(s):

Maria Paula da Silva ◽

Lino A. Sander de Carvalho ◽

Evlyn Novo ◽

Daniel S. F. Jorge ◽

Claudio C. F. Barbosa

Keyword(s):

Remote Sensing ◽

Organic Matter ◽

Dissolved Organic Matter ◽

Seasonal Variability ◽

Large Scale ◽

River Bank ◽

In Situ Data ◽

Amazon Floodplain ◽

Significant Difference

Abstract. Given the importance of DOM in the carbon cycling of aquatic ecosystems, information on its seasonal variability is crucial. This study assesses the use of available absorption optical indices based on in situ data to both characterize the seasonal variability of the DOM dynamics in a highly complex environment and their viability of being used for satellite remote sensing on large scale studies. The study area comprises four lakes located at the Mamirauá Sustainable Development Reserve (MSDR). Samples for the determination of coloured dissolved organic matter (CDOM) and remote sensing reflectance (Rrs) were acquired in situ. The Rrs was applied to simulate MSI visible bands and used in the proposed models. Differences between lakes were tested regarding CDOM indices. Significant difference in the average of aCDOM (440), aCDOM spectra and S275–295 were found between lakes located inside the flood forest and those near the river bank. The proposed model showed that aCDOM can be used as proxy of S275–295 during rising water with good validation results, demonstrating the potential of Sentinel/MSI imagery data in large scale studies on the dynamics of DOM.

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Monitoring seasonal variations of colored dissolved organic matter for the Saginaw River based on Landsat-8 data

Water Science & Technology Water Supply ◽

10.2166/ws.2018.077 ◽

2018 ◽

Vol 19 (1) ◽

pp. 274-281 ◽

Cited By ~ 6

Author(s):

Jiang Chen ◽

Weining Zhu ◽

Yuhan Zheng ◽

Yong Q. Tian ◽

Qian Yu

Keyword(s):

Remote Sensing ◽

Organic Matter ◽

Environmental Factors ◽

Dissolved Organic Matter ◽

Spatial Resolution ◽

Seasonal Variations ◽

Pearson Correlation ◽

Landsat 8 ◽

Colored Dissolved Organic Matter ◽

Positive Role

Abstract Remote sensing is an effective tool for studying CDOM (colored dissolved organic matter) variations and its relevant environmental factors. Monitoring CDOM distribution and dynamics in small water is often limited by the coarse spatial resolution of traditional ocean color sensors. In this study, because of its high spatial resolution of 30 m, Landsat-8 data were used to assess seasonal variations of CDOM in the Saginaw River, by using an empirical statistic model. Pearson correlation analysis between CDOM variations and other environmental factors, such as temperature, discharge, and dissolved oxygen, shows that temperature was negatively correlated to CDOM variations and discharge played a positive role. We also calculated the monthly mean aCDOM(440) (the absorption coefficient of CDOM at 440 nm) for the Saginaw River between April and November from 2013 to 2016. This study demonstrates a good example for future applications in small waters: observing CDOM variations and other relevant environmental factors change by using Landsat remote sensing, so that we can know more about water quality and ecosystem health of small waters as well as the climate change impact on regional watersheds.

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